A computerized database as decision support tool for the selection of agroforestry tree species

1994 ◽  
Vol 26 (1) ◽  
pp. 65-70 ◽  
Author(s):  
J. -M. Schr�der ◽  
H. Jaenicke
Keyword(s):  
Decision Support ◽  
Tree Species ◽  
Decision Support Tool ◽  
Support Tool ◽  
Selection Of

scholarly journals Decision support criteria and the development of a decision support tool for the selection of conservation materials for the built cultural heritage

2019 ◽  
Vol 37 ◽  
pp. 44-53 ◽  
Author(s):  
Janez Turk ◽  
Alenka Mauko Pranjić ◽  
Andrew Hursthouse ◽  
Robert Turner ◽  
John J. Hughes
Keyword(s):  
Decision Support ◽  
Cultural Heritage ◽  
Decision Support Tool ◽  
Support Tool ◽  
Selection Of

scholarly journals A DECISION SUPPORT TOOL ON DERELICT BUILDINGS FOR URBAN REGENERATION

2018 ◽  
Vol IV-4/W7 ◽  
pp. 19-25
Author(s):  
I. Blečić ◽  
A. Cecchini ◽  
M. Minchilli ◽  
L. F. Tedeschi ◽  
G. A. Trunfio
Keyword(s):  
Decision Support ◽  
Economies Of Scale ◽  
Search Algorithm ◽  
Urban Regeneration ◽  
Decision Support Tool ◽  
Support Tool ◽  
Area Of Interest ◽  
The City ◽  
Selection Of

<p><strong>Abstract.</strong> We present a decision suppport tool for the comparison and selection of projects of integrated renovation of derelict buildings and areas for the purpose of urban regeneration. Each project is defined as a subset of derelict properties to renovate together with their respective designated use, and is scored by the decision support tool on two criteria: expected effort and estimated effectiveness in terms of improved urban capabilities in the urban area of interest. The expected effort is estimated as a global transformation cost, factoring in legal and management overhead costs as well as possible economies of scale. The effectiveness in evaluated in terms of extension of urban capabilities centred on walkable distances. We have implemented a bi-objective evolutionary search algorithm to address the computational complexity of the problem of search for efficient (non-dominated) projects over the two criteria. For the purpose of illustration, we present an example case-study application on the historical core of the city of Sassari, Italy.</p>

scholarly journals Decision support for the selection of reference sites using <sup>137</sup>Cs as a soil erosion tracer

SOIL ◽  
2017 ◽  
Vol 3 (3) ◽  
pp. 113-122 ◽  
Author(s):  
Laura Arata ◽  
Katrin Meusburger ◽  
Alexandra Bürge ◽  
Markus Zehringer ◽  
Michael E. Ketterer ◽  
...  
Keyword(s):  
Decision Support ◽  
Soil Erosion ◽  
Decision Tree ◽  
Decision Support Tool ◽  
Small Scale ◽  
Reference Sites ◽  
Chernobyl Fallout ◽  
Support Tool ◽  
Alpine Valley ◽  
Selection Of

Abstract. The classical approach of using 137Cs as a soil erosion tracer is based on the comparison between stable reference sites and sites affected by soil redistribution processes; it enables the derivation of soil erosion and deposition rates. The method is associated with potentially large sources of uncertainty with major parts of this uncertainty being associated with the selection of the reference sites. We propose a decision support tool to Check the Suitability of reference Sites (CheSS). Commonly, the variation among 137Cs inventories of spatial replicate reference samples is taken as the sole criterion to decide on the suitability of a reference inventory. Here we propose an extension of this procedure using a repeated sampling approach, in which the reference sites are resampled after a certain time period. Suitable reference sites are expected to present no significant temporal variation in their decay-corrected 137Cs depth profiles. Possible causes of variation are assessed by a decision tree. More specifically, the decision tree tests for (i) uncertainty connected to small-scale variability in 137Cs due to its heterogeneous initial fallout (such as in areas affected by the Chernobyl fallout), (ii) signs of erosion or deposition processes and (iii) artefacts due to the collection, preparation and measurement of the samples; (iv) finally, if none of the above can be assigned, this variation might be attributed to turbation processes (e.g. bioturbation, cryoturbation and mechanical turbation, such as avalanches or rockfalls). CheSS was exemplarily applied in one Swiss alpine valley where the apparent temporal variability called into question the suitability of the selected reference sites. In general we suggest the application of CheSS as a first step towards a comprehensible approach to test for the suitability of reference sites.

scholarly journals TURNING LOCAL KNOWLEDGE ON AGROFORESTRY INTO AN ONLINE DECISION-SUPPORT TOOL FOR TREE SELECTION IN SMALLHOLDERS’ FARMS

2016 ◽  
Vol 55 (S1) ◽  
pp. 50-66 ◽  
Author(s):  
JUST VAN DER WOLF ◽  
LAURENCE JASSOGNE ◽  
GIL GRAM ◽  
PHILIPPE VAAST
Keyword(s):  
Decision Support ◽  
Ecosystem Services ◽  
Tree Species ◽  
Smallholder Farmers ◽  
Decision Support Tool ◽  
Agroforestry Systems ◽  
Species Selection ◽  
Adaptation To Climate Change ◽  
Local Conditions ◽  
Support Tool

SUMMARYThis paper presents the main features of a unique decision-support tool developed for selecting tree species in coffee and cocoa agroforestry systems. This tool aims at assisting in the selection of appropriate shade trees taking into account local conditions as well as needs and preferences of smallholder farmers while maximizing ecosystem services from plot to landscape level. This user-friendly and practical tool provides site-specific recommendations on tree species selection via simple graphical displays and is targeted towards extension services and stakeholders directly involved in sustainable agroforestry and adaptation to climate change. The tool is based on a simple protocol to collect local agroforestry knowledge through farmers’ interviews and rankings of tree species with respect to locally perceived key ecosystem services. The data collected are first analysed using the BradleyTerry2 package in R, yielding the ranking scores that are used in the decision-support tool. Originally developed for coffee and cocoa systems of Uganda and Ghana, this tool can be extended to other producing regions of the world as well as to other cropping systems. The tool will be tested to see if repeated assessments show consistent ranking scores, and to see if the use of the tool by extension workers improves their shade tree advice to local farmers.

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